How To Plan A Schedule On A Computer (For Microsoft)

Transcription

1 Chapter 5: Process Scheduling Objectives To introduce CPU scheduling To describe various CPU-scheduling algorithms To discuss evaluation criteria for selecting the CPU-scheduling algorithm for a particular system Chapter 5: Process Scheduling Basic Concepts Scheduling Criteria Scheduling Algorithms Multiple-Processor Scheduling Operating Systems Examples (Linux) Algorithm Evaluation Skip: 5.4.2, 5.5.4, Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne Basic Concepts Histogram of CPU-burst Times Maximum CPU utilization obtained with multiprogramming CPU I/O Burst Cycle Process execution consists of a cycle of CPU execution and I/O wait 5.3 Silberschatz, Galvin and Gagne 2005 CPU burst distribution 5.4 Silberschatz, Galvin and Gagne 2005

2 CPU Scheduler Dispatcher Selects from among the processes in memory that are ready to execute, and allocates the CPU to one of them CPU scheduling decisions may take place when a process: 1. Switches from running to waiting state 2. Switches from running to ready state 3. Switches from waiting to ready 4. Terminates Scheduling only under 1 and 4 is nonpreemptive All other scheduling is preemptive Dispatcher module gives control of the CPU to the process selected by the short-term scheduler; this involves: switching context switching to user mode jumping to the proper location in the user program to restart that program Dispatch latency time it takes for the dispatcher to stop one process and start another running 5.5 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne Scheduling Criteria Optimization Criteria correct p.188 CPU utilization keep the CPU as busy as possible Throughput # of processes that complete their execution per time unit Turnaround time amount of time to execute a particular process Waiting time amount of time a process has been waiting in the ready queue Response time amount of time it takes from when a request was submitted until the first response is produced, not output (for time-sharing environment) The response time is generally limited by the speed of the output device 5.7 Silberschatz, Galvin and Gagne 2005 Max average CPU utilization Max average throughput Min average turnaround time Min average waiting time Min average response time Under some circumstances Optimize the max or min values, rather than the average. Like minimize the max response time minimize the variance for predictable outcome 5.8 Silberschatz, Galvin and Gagne 2005

3 5.3 Scheduling Algorithms 531Fi First-Come, tc First-Served (FCFS) Scheduling In the following consider only one CPU burst Process Burst Time P 1 24 P 2 3 P 3 3 Suppose that the processes arrive in the order: P 1, P 2, P 3. The Gantt Chart for the schedule is: 0 P 1 P 2 P Waiting time for P 1 = 0; P 2 = 24; P 3 = 27 Average waiting time: ( )/3 = 17 FCFS Scheduling (Cont.) Suppose that the processes arrive in the order P 2, P 3, P 1 The Gantt chart for the schedule is: 0 P 2 P 3 P Waiting time for P 1 = 6;P 2 = 0 ; P 3 = 3 Average waiting time: ( )/3 = 3 Much better than previous case Convoy effect short process behind long process Nonpreemptive 5.9 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne Shortest-Job-First (SJR) Scheduling Example of Non-Preemptive SJF Associate with each process the length of its next CPU burst. Use these lengths to schedule the process with the shortest time Two schemes: nonpreemptive once CPU given to the process it cannot be preempted until completes its CPU burst preemptive if a new process arrives with CPU burst length less than remaining time of current executing process, preempt. This scheme is know as the Shortest-Remaining-Time-First (SRTF) SJF is optimal gives minimum average waiting time for a given set of processes Process Arrival Time Burst Time P P P P SJF (non-preemptive) P 1 P 3 P 2 P Average waiting time = ( )/4 = Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005

4 Example of Preemptive SJF Process Arrival Time Burst Time SJF (preemptive) P P P P P 1 P 2 P 3 P 2 P 4 P 1 Determining Length of Next CPU Burst Can only estimate the length Estimation can be done by using the length of previous CPU bursts, using exponential averaging th 1. t n = actual lenght of n CPU burst 2. τ n = predicted value for the next CPU burst α, 0 α 1 ( ) 4. Define : τ n= 1 = α tn + ( 1 α ) τ n Average waiting time = ( )/4 = Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005 Prediction of the Length of the Next CPU Burst Examples of Exponential Averaging α =0 τ n+1 = τ n Recent history does not count α =1 τ n+1 = α t n Only the actual last CPU burst counts If we expand the formula, we get: τ n+1 = α t n +(1 - α)α t n (1 - α ) j α t n -j + +(1 - α ) n +1 τ 0 shift p.191 Since both α and (1 - α) are less than or equal to 1, each successive term has less weight than its predecessor 5.15 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005

5 5.3.3 Priority Scheduling A priority number (integer) is associated with each process The CPU is allocated to the process with the highest priority (smallest integer means highest priority) Preemptive nonpreemptive SJF is a priority scheduling where priority is the inverse of the predicted next CPU burst time Priority could be defined internally or externally Problem of Starvation low priority processes may never execute Solution: Aging as time progresses increase the priority of the process Round Robin (RR) Each process gets a small unit of CPU time (time quantum), ) usually milliseconds. After this time has elapsed, the process is preempted and added to the end of the ready queue. If there are n processes in the ready queue and the time quantum is q, then each process gets 1/n of the CPU time in chunks of at most q time units at once. No process waits more than (n-1)*q time units. Performance q large FIFO q small q must be large with respect to context switch, otherwise overhead is too high 5.17 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005 Example of RR with Time Quantum = 4 Process Burst Time P 1 24 P 2 3 P 3 3 The Gantt chart is: P 1 P 2 P 3 P 1 P 1 P 1 P 1 P Average waiting time = (6+4+7)/3 Another Example of RR with Time Quantum = 20 Process Burst Time P 1 53 P 2 17 P 3 68 P 4 24 The Gantt chart is: P 1 P 2 P 3 P 4 P 1 P 3 P 4 P 1 P 3 P Average waiting time =( )/4 Typically, higher average turnaround than SJF, but better response 5.19 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005

6 Time Quantum and Context Switch Time Turnaround Time Varies With The Time Quantum Typically, most OS have time quanta from 10 to 100 milliseconds, and have context switch time less than 10 microseconds The average turnaround time does not necessary improve as the time-quantum size increases 5.21 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne Multilevel Queue Multilevel Queue Scheduling Ready queue is partitioned into separate queues For example: foreground (interactive) and background (batch) Each queue has its own scheduling algorithm foreground RR background FCFS Scheduling must be done between the queues Fixed priority it scheduling; (i.e., serve all from foreground then from background). Possibility of starvation. Time slice each queue gets a certain amount of CPU time which it can schedule amongst its processes; For example, 80% to foreground in RR, and 20% to background in FCFS 5.23 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005

7 5.3.6 Multilevel Feedback Queue Example of Multilevel Feedback Queue A process can move between the various queues; aging can be implemented this way Multilevel-feedback-queue scheduler defined by the following parameters: number of queues scheduling algorithms for each queue method used to determine when to upgrade a process method used to determine when to demote a process method used to determine which queue a process will enter when that process needs service Three queues: Q 0 RR with time quantum 8 milliseconds Q 1 RR time quantum 16 milliseconds Q 2 FCFS Scheduling A Anew job enters queue Q 0 which h is served FCFS. When it gains CPU, job receives 8 milliseconds. If it does not finish in 8 milliseconds, job is moved to queue Q 1. At Q 1 job is again served FCFS and receives 16 additional milliseconds. If it still does not complete, it is preempted and moved to queue Q Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne Thread Scheduling Distinction between user-level and kernel-level threads Many-to-one and many-to-many models, thread library schedules user-level threads to run on LWP Known as process-contention contention scope (PCS) since scheduling competition is within the process Kernel thread scheduled onto available CPU is system-contention scope (SCS) competition among all threads in system 5.5 Multiple-Processor Scheduling CPU scheduling more complex when multiple CPUs are available Homogeneous processors within a multiprocessor We can use any available processor to run any process Load sharing Approaches Asymmetric multiprocessing only one processor accesses the system data structures, alleviating i the need for data sharing Symmetric multiprocessing (SMP) each processor is self-scheduling Skip Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005

8 Processor Affinity Cache memory concerns If a process migrates from one processor to another, then the content of cache memory must be invalidated in the first processor and re-populated in the second processor Processor affinity: a process tends to stay in the same processor on which it is currently running Load Balancing Keep the workload evenly distributed across all processors Approaches Push migration Pull migration Skip 5.5.4, Silberschatz, Galvin and Gagne Algorithm Evaluation Deterministic modeling takes a particular predetermined workload and defines the performance of each algorithm for that workload Useful for cases where the same program runs over and over Queueing models mathematical formula to describe the distribution of CPU and I/O bursts, the process arrival time Little s formula: In a steady state, the number of processes leaving the system is equal to the number of processes arriving the system avearge number of leaving n = λ W arriving rate average wait time 5.30 Silberschatz, Galvin and Gagne 2005 Simulation Implementation The only complete accurate way to evaluate a scheduling algorithm. Difficulties: High cost: coding and user reaction Changing environment: users will find out and switch Most flexible scheduling Fine tunable for specific applications Provide a command (like dispadmin in Solaris) to allow system administrators to modify the scheduling parameters Provide API to modify the priority of a process 5.31 Silberschatz, Galvin and Gagne Silberschatz, Galvin and Gagne 2005